In an enterprise, data is generated from all the software that is participating in day-to-day operations. This data has different formats, and bringing in this data for big-data processing requires a storage system that is flexible enough to accommodate a data with varying data models. A NoSQL database, by its design, is best suited for this kind of storage requirements. One of the primary objectives of NoSQL is horizontal scaling, that is, the P in CAP theorem, but this works at the cost of sacrificing Consistency or Availability. Visit http://en.wikipedia.org/wiki/CAP_theorem to understand more about CAP theorem.
Scaling Big Data with Hadoop and Solr, Second Edition
By :
Scaling Big Data with Hadoop and Solr, Second Edition
By:
Overview of this book
Table of Contents (13 chapters)
Scaling Big Data with Hadoop and Solr Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Processing Big Data Using Hadoop and MapReduce
Understanding Apache Solr
Enabling Distributed Search using Apache Solr
Big Data Search Using Hadoop and Its Ecosystem
Scaling Search Performance
Use Cases for Big Data Search
Index
Customer Reviews